Departamento de Estadística
http://hdl.handle.net/10016/12
2015-12-01T05:42:35ZRobust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk
http://hdl.handle.net/10016/22035
Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk
Hotta, Luiz; Trucíos, Carlos; Ruiz, Esther
Universidad Carlos III de Madrid. Departamento de Estadística
Bootstrap procedures are useful in GARCH models to obtain forecast densities for returns and volatilities.In this paper, we analyze the effect of outliers on the finite sample properties of these densities when they are based on standard maximum likelihood and robust procedures. We show that when the former procedure is implemented, the bootstrap densities are badly affected by the presence of outliers. However,the robust estimator based on variance targeting with an adequate modification of the volatility filter has the best performance when compared with alternative robust procedures. The results are illustrated withboth simulated and real data
2015-11-01T00:00:00ZPure threshold strategies for a two-node tandem network under partial information
http://hdl.handle.net/10016/21703
Pure threshold strategies for a two-node tandem network under partial information
D'Auria, Bernardo; Kanta, Spyridoula
In a two node tandem network, customers decide to join or balk by maximizing a given profit function whose costs are proportional to the sojourn time they spend at each queue. Assuming that their choicesare taken without knowing the complete state of the system, we show that a pure threshold equilibrium policy exists. In particular we analyze the case when the partial information consists in informing the arrival customers of the total number of users in the network.
2015-09-01T00:00:00ZRetail competition with switching consumers in electricity markets
http://hdl.handle.net/10016/21918
Retail competition with switching consumers in electricity markets
Ruiz Mora, Carlos; Nogales Martín, Francisco J.; Prieto Fernández, Francisco Javier
Universidad Carlos III de Madrid. Departamento de Estadística
The ongoing transformations of power systems worldwide pose important challenges,both economic and technical, for their appropriate planning and operation. A key approach to improve the efficiency of these systems is through demand-side management, i.e., to promote the active involvement of consumers in the system. In particular, the current trend it to conceive systems where electricity consumers can vary their load according to real-time price incentives, offered by retailing companies.Under this setting, retail competition plays an important role as inadequate prices orservices may entail consumers switching to a rival retailer. In this work we consider a game theoretical model where asymmetric retailers compete in prices to increase their profits by accounting for the utility function of consumers. Consumer preferences for retailers are uncertain and distributed within a Hotelling line. We analytically characterize the equilibrium of a retailer duopoly, establishing its existence and uniqueness conditions. Furthermore, sensitivities of the equilibrium prices with respect to relevant model parameters are also provided. The duopoly model is extended to a multiple retailer case for which we perform an empirical analysis via numerical simulations. Results indicate that, depending on the retailer costs, loyalty rewards and initial market shares, the resulting equilibrium can range from complete competition to one in which a retailer have a leading or even a dominant position in the market, decreasing the consumers' utility significantly. Moreover, the retailer network configuration also plays an important role in the competitiveness of the system
2015-11-01T00:00:00ZPortfolio selection with proportional transaction costs and predictability
http://hdl.handle.net/10016/21882
Portfolio selection with proportional transaction costs and predictability
Mei, Xiaoling; Nogales Martín, Francisco Javier
Universidad Carlos III de Madrid. Departamento de Estadística
We consider the portfolio optimization problem for a multiperiod investor who seeks to maximize her utility of consumption facing multiple risky assets and proportional transaction costs in the presence of return predictability. Due to the curse of dimensionality, this problem is very difficult to solve even numerically. In this paper, we propose several feasible policies that are based on optimizing quadratic programs. These proposed feasible policies can be easily computed even for many risky assets. We show how to compute upper bounds and use them to study how the losses associated with using the approximate policies depend on different problem parameters.
2015-11-01T00:00:00Z